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Hypothesis testClassical statistics

Effect Size Analysis

Kiwango cha p kinaweza kufikia umuhimu na athari ndogo ikiwa sampuli ni kubwa vya kutosha, hata hivyo matokeo yanaweza kuwa hayana maana ya vitendo. Ukubwa wa athari hutatua hili kwa kueleza ukubwa wa tofauti au uhusiano katika kitengo cha kawaida — kupotoka kwa kiwango, sehemu za utofauti ulioelezewa, au uwezekano wa ubora. Cohen's d inakuambia ni upotokaji mangapi wa kiwango kati ya maana mbili za kikundi; eta-squared na omega-squared zinakuambia ni sehemu gani ya utofauti jumla ambayo sababu inaeleza; r inafupisha nguvu ya uhusiano wa pande mbili. Viashirio hivi vyote hufanya kazi kwa kujitegemea kutoka kwa N, na kuviwezesha kuwa muhimu kwa upangaji wa nguvu na meta-uchanganuzi.

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Vyanzo

  1. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832
  2. Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4, 863. DOI: 10.3389/fpsyg.2013.00863

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Effect Size Analysis. ScholarGate. https://scholargate.app/sw/statistics/effect-size-analysis

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Imerejelewa na

ScholarGateEffect size analysis (Effect Size Analysis). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/statistics/effect-size-analysis · Seti ya data: https://doi.org/10.5281/zenodo.20539026